Weather is one of the major causes of general aviation accidents. Researchers are addressing this problem from various perspectives including improving meteorological forecasting techniques, collecting additional weather data automatically via on-board sensors and "flight" modems, and improving weather data dissemination and presentation. We approach the problem from the improved presentation p...

Thermal building simulation currently uses Typical Meteorological Year (TMY) data to guide the design decision-making process or for compliance with energy standards. TMY data usually excludes extremes and in many cases are gathered from microclimatic contexts that are not sufficiently representative of the project sites (e.g., airports), adding uncertainty in the analyses. To enable a quantifi...

The knowledge of weather is useful for finding climate change over a period. In this present frame work uses 15 years of weather of Hyderabad city , data a real time the datasets collected from weather station. Weather data is a time series and multidimensional data. Outliers are the objects whose behavior is different from the rest. Outliers in weather data represent the cyclone, drought, seas...

approved: Prasad Tadepalli Severe weather in the United States causes huge insured losses to crop and property frequently. It creates major impact and elicit diverse response in the weather insurance industry. Events like hail, storm, hurricane etc. are more likely to cause catastrophe losses. So it becomes crucial to collect and analyze these extreme weather information. Thus, weather data col...

Functional Data Analysis (FDA) has recently made considerable progress because of easier access to the data that are essentially in the form of curves. Although functional modeling of Iranian precipitation based on temperature or humidity was done before, here we use functional analysis of variance and covariance to analyze the weather data collected randomly from Iranian weather stations in 20...

In this article, we apply the independent component analysis technique for mining spatio-temporal data. The technique has been applied to mine for patterns in weather data using the North Atlantic Oscillation (NAO) as a specific example. We find that the strongest independent components match the observed synoptic weather patterns corresponding to the NAO. We also validate our results by matchi...

This paper considers only the IRS mission, for which the highest priority is on atmospheric dynamics in support to Numerical Weather Prediction (NWP) at regional and global scales. This will be achieved through the provision of Atmospheric Motion Vectors (AMV), to be extracted from tracking of horizontally and vertically resolved water vapour patterns, retrieved from the hyperspectral radiances...